Thesis Type: Post Graduate
Institution Of The Thesis: Middle East Technical University, Graduate School of Natural and Applied Sciences, Turkey
Approval Date: 2019
Thesis Language: English
Student: AHMET BAHADIR KOÇ
Principal Consultant (For Co-Consultant Theses): Murat Altuğ Erberik
Co-Consultant: Ayşegül Askan GündoğanAbstract:
Over the centuries, strong seismic activities have occurred with uncertain frequencies in the world which caused earthquake-prone regions to be severely influenced in terms of structural damage and economic losses. Therefore, seismic assessment approaches have been developed to minimize the vulnerability of structures, to carry out pre-earthquake mitigation planning and to mitigate economic losses. This study mainly focuses on the performance estimation of unreinforced masonry (URM) structures using synthetic ground motions, which are based on the simulated 1999 Düzce Earthquake. The performance values of the structural parameters for URM structures have been obtained in accordance with earthquake design specifications and literature reviews and also represent their local characteristics. The equivalent single-degree-of-freedom (SDOF) models are generated to simplify inelastic dynamic analysis by using these parameters. The synthetic ground motion records are generated in the case study Düzce region, by considering different earthquake scenarios, soil conditions and source-to-site distances. The seismic responses of structural simulations represent base shear versus displacement relationship. By comparing the results of displacement obtained from inelastic dynamic analyses and the pre-defined limit states, the damage states (DS) of URM structures are determined. At the end of the study, the sensitivity of the structural parameters, the estimation of performance levels under different magnitude and PGA values and the relationships between DS and independent variables, which comprise seismological and structural parameters, are carried out and the obtained results are interpreted by using probabilistic and statistical approaches.